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Record W2766645990 · doi:10.1002/lom3.10221

Open the Sterivex<sup>TM</sup> casing: An easy and effective way to improve DNA extraction yields

2017· article· en· W2766645990 on OpenAlexaff
Perrine Cruaud, Adrien Vigneron, Marie‐Stéphanie Fradette, Steve J. Charette, Manuel J. Rodríguez, Caetano C. Dorea, Alexander I. Culley

Bibliographic record

VenueLimnology and Oceanography Methods · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsUniversity of VictoriaInstitut universitaire de cardiologie et de pneumologie de QuébecUniversité Laval
Fundersnot available
KeywordsCartridgeExtraction (chemistry)CasingDNA extractionDNAProtocol (science)Filter (signal processing)ChromatographyComputer scienceBiological systemMaterials scienceComputational biologyChemistryBiologyEngineeringPolymerase chain reactionBiochemistryGeneMedicine

Abstract

fetched live from OpenAlex

Abstract We describe an inexpensive, reliable, and easily executed improvement for the extraction of DNA from SterivexTM filter units, that involves the separation of the SterivexTM filter from its casing. Our study demonstrates that our modification of the original extraction protocol significantly increased DNA yields, with an average increase of 4.1‐fold more DNA than with the standard approach. A comparison of the diversity after Illumina MiSeq sequencing of bacterial communities extracted with both the standard approach and the proposed one indicated that our modified protocol has no or little impact on the results. This protocol provides a relatively straight forward means to achieve higher yields of DNA from the extraction of SterivexTM cartridges without altering the community composition and will likely be of interest to a wide range of scientists that use techniques based on the recovery of DNA from filters.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.009

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.358
Teacher spread0.329 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations89
Published2017
Admission routes1
Has abstractyes

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